地震系统
地震救援地震预警系统

地震救援地震预警系统地震是一种自然灾害,对人们的生命财产安全造成严重威胁。
为了提高地震灾害的防范能力和减轻灾害的损失,地震预警系统应运而生。
地震预警系统是基于地震监测数据,通过实时分析震波传播速度和地震能量释放预测地震发生时间、地点和强度的系统。
本文将全面介绍地震救援地震预警系统的原理、运行机制和应用前景。
一、地震救援地震预警系统的原理地震预警系统是通过实时监测地震波的传播速度和地震能量释放来预测地震发生时间、地点和强度。
地震波的传播速度与地震震源距离有关,在地震波传播过程中,可以通过监测到的前震波速度来预测地震的剩余震动时间。
当地震波传播达到一定距离时,地震预警系统会向地震发生区域的人们发送预警信号,提醒他们采取防护措施。
二、地震救援地震预警系统的运行机制地震预警系统是由地震监测设备、数据传输系统和预警台站等组成的。
地震监测设备主要包括地震传感器和数据采集器,用于实时监测地震波的传播和能量释放等信息。
数据传输系统将监测到的地震数据传输给预警台站,预警台站通过分析处理地震数据,判断地震发生的可能性,并向地震发生区域发送预警信号。
地震发生后,地震预警系统还可以提供相关的紧急救援信息,帮助救援人员快速到达灾区进行救援。
三、地震救援地震预警系统的应用前景地震预警系统在地震灾害的防控中起到了重要作用。
首先,地震预警系统可以提前几秒到几十秒发出预警,为人们逃生和采取避灾措施争取了珍贵时间。
其次,地震预警系统还可以向救援人员发送预警信号,以确保救援行动的及时性和有效性。
此外,地震预警系统还可以为地震科学研究提供重要的数据支持,帮助科学家更好地理解地震的规律和机制,为地震灾害的预测和防范提供科学依据。
总结起来,地震救援地震预警系统是一项重要的科技创新,对于提高地震灾害的防范和减轻灾害损失起到了不可替代的作用。
随着技术的不断发展和完善,地震预警系统的应用前景将会更加广阔,为保护人们的生命财产安全做出更大的贡献。
地球科学中的地震预警系统

地球科学中的地震预警系统地震是一种自然灾害,可以在短时间内造成极大的破坏和人员伤亡。
为了减轻地震带来的损失,科学家们开发了地震预警系统,可以提前几秒钟或几分钟发出警报,让人们有更多的时间采取行动。
本文将介绍地球科学中的地震预警系统,包括其工作原理、应用场景和发展趋势。
一、工作原理地震预警系统的工作原理主要是利用地震波在地球内部传播的速度和传播路径来预测地震的发生和强度。
当地震波在地球内部传播时,会沿着不同的路径传播,不同的路径会有不同的传播速度。
地震预警系统可以利用这种差异来确定地震的位置和规模。
地震预警系统通常由三个部分组成:地震台网、地震传感器和中央控制中心。
地震台网是一组分布在地球表面的地震台站,用于检测地震波。
地震传感器则是安装在地面或地下的仪器,用于测量地震波的振动和速度。
中央控制中心则是地震预警系统的核心,它通过收集地震波的数据、计算地震的位置和规模,并发出警报通知人们采取适当的行动。
二、应用场景地震预警系统可以被广泛应用于地震灾害管理和公共安全领域。
以下是一些典型的应用场景:1. 建筑结构安全:地震预警系统可以帮助建筑师设计更安全的建筑结构,以便在地震发生时减少人员伤亡和财产损失。
2. 公共交通安全:地震预警系统可以在地震发生时自动停止地铁和高速公路的运行,避免人员和车辆遭受损失。
3. 能源安全:地震预警系统可以帮助电力和石油工业采取适当的措施,以避免设备损坏和停产造成的影响。
4. 航空安全:地震预警系统可以提醒航空公司飞行员有地震风险,以便他们采取适当的行动,例如选择避开地震区域的航线。
三、发展趋势目前,地震预警系统已经被广泛应用于许多国家和地区。
随着新技术和新方法的不断出现,地震预警系统的性能和可靠性也在不断提高。
以下是一些地震预警系统的未来发展趋势:1. 人工智能:随着人工智能技术的不断发展,智能地震预警系统将会出现。
这种系统可以通过机器学习技术自动识别地震波,为地震预警系统的识别速度和准确性带来进一步提高。
地震预警系统的原理与应用

地震预警系统的原理与应用地震是自然界中一种极具破坏力的自然灾害,给人们的生命财产安全带来了巨大威胁。
在地震发生前能够提前几秒、几分钟甚至更长时间发出预警,可以为人们采取避险措施提供宝贵时间,减少灾害造成的损失。
地震预警系统作为现代科技的产物,通过对地震前兆现象进行监测和分析,实现了对地震的提前预警。
本文将深入探讨地震预警系统的原理及其在实际应用中的价值。
1. 地震预警系统的基本原理地震预警系统基本原理是通过监测地震前兆信号,包括P波和S 波的到达时间差、地表位移、速度和加速度等数据,来判断地震发生的可能性和强度。
其中,P波是最快传播的纵波,能够提供最早的地震信息;S波是横波,传播速度次于P波。
通过测量P波和S波的到达时间差,可以计算出地震发生的距离和规模。
另外,地表位移、速度和加速度等参数也是判断地震强度和影响范围的重要依据。
2. 地震预警系统的构成及工作流程通常,地震预警系统由地震监测装置、数据传输通道、数据处理中心和预警信息发布平台四个主要部分构成。
当地震监测装置捕捉到地震前兆信号后,将数据传输到数据处理中心进行实时分析和处理。
数据处理中心通过算法对地震参数进行计算,并根据预设的标准判断是否触发预警信号。
一旦确认地震即将来临,预警信息将通过发布平台发送给公众。
3. 地震预警系统在实际应用中的意义3.1 降低人员伤亡和财产损失地震预警系统可以在地震发生前数秒至数分钟内发出预警信号,为人们提供紧急疏散或躲避的时间窗口,有效降低人员伤亡和财产损失。
3.2 改善城市社会运行方式城市集聚了大量人口和财富,如能够提供准确可靠的地震预警服务,可以保障城市社会基础设施运行安全,维护社会秩序。
3.3 促进灾后救援和恢复工作地震预警系统为灾后救援提供了重要支撑,在短时间内快速响应、组织救援力量,有效减轻救援压力, 提高救援效率。
4. 地震预警系统的发展趋势随着科技的不断进步和国际合作的不断加强,地震预警系统将更加智能化和精准化。
地震预警系统

地震预警系统地震是一种自然灾害,给人们的生命和财产安全造成了巨大威胁。
为了能够更好地应对地震风险,发展地震预警系统成为了迫切的需求。
地震预警系统是一种通过监测地震前兆,提前发出警报并向相关地区发送预警信息,以便人们采取适当措施来减轻地震带来的损失的工具。
一、地震预警系统的原理和技术地震预警系统的核心是快速准确地探测地震前兆并及时判断地震的特征,以便尽早发出预警。
该系统主要基于地震监测和地震学原理,利用地震仪、加速度计等设备来实时监测地震的震源位置和震级,并通过地震波传播速度来预测地震到达的时间。
其中,地震仪可以测量地震波的震动,而加速度计则可以测量地壳的加速度变化。
同时,地震预警系统还结合了地震数据分析、人工智能和通信技术等多种技术手段,以提高地震预警的准确性和及时性。
二、地震预警系统的工作流程地震预警系统的工作流程主要分为地震监测、数据处理和预警发布三个步骤。
首先,地震监测阶段通过地震仪、加速度计等设备实时采集地震数据,然后将数据传输到数据处理中心进行处理。
数据处理中心利用地震学算法对地震数据进行分析和判断,以确定地震的震级、震源位置和预测地震到达的时间。
最后,在预警发布阶段,系统将预警信息通过短信、互联网等渠道迅速发送到相关地区,以便人们及时采取应对措施。
三、地震预警系统的应用价值地震预警系统为人们提供了宝贵的预警时间,可以帮助人们采取适当的避难措施,减少地震灾害造成的人员伤亡和财产损失。
首先,地震预警系统可以在地震发生前几秒至几十秒的时间内提供预警信息,为人们避免危险区域、寻找避难场所争取时间。
其次,地震预警系统还可以帮助人们判断地震的严重程度,指导相关部门进行紧急救援和灾后重建工作。
最后,地震预警系统的建设和应用还可以提高社会的地震意识和应对能力,促进地震灾害防治的科学化和规范化。
四、地震预警系统的发展现状和前景目前,地震预警系统在世界范围内已经得到广泛应用。
日本、美国、墨西哥等地区的地震预警系统已经取得了较好的效果,并在地震发生后的救援和重建工作中发挥了重要作用。
地震学中的地震预警系统

地震学中的地震预警系统地震,作为自然界最为破坏力强大的自然灾害之一,常常带来巨大的人员伤亡和财产损失。
然而,随着科技的不断发展,地震学中的地震预警系统正逐渐成为减轻地震灾害影响的有效手段。
本文将介绍地震学中的地震预警系统及其应用,帮助读者更好地了解和利用这一技术。
一、地震预警系统的原理地震预警系统是通过检测地震波到达的时间差来预测地震的强度和到达时间,从而提前进行相应的预警措施。
具体而言,地震预警系统主要通过以下几个步骤来实现:1. 传感器网络:地震预警系统利用部署在地壳各处的传感器网络来监测地震波的传播情况。
这些传感器可以感知到地震波的到达时刻,并将数据传输至中心处理系统。
2. 数据传输与处理:传感器所采集到的地震波信息会通过无线或有线方式传输至地震预警中心,然后由中心处理系统对数据进行分析和处理。
3. 预警发布:当中心处理系统分析判断出地震波的传播趋势时,将会发送预警信息至目标区域,通知受影响的人们采取相应的应对措施。
二、地震预警系统的应用地震预警系统的应用可以分为个人和公共两个层面。
个人层面的应用主要包括以下几个方面:1. 保护人身安全:地震预警系统可以提前几秒到几十秒甚至更长时间发出预警信号,让人们有时间采取避险措施,从而有效保护人身安全。
2. 减少财产损失:地震预警系统的存在,可以让人们提前关停设备、转移贵重物品等,从而降低地震造成的财产损失。
公共层面的应用主要包括以下几个方面:1. 政府决策支持:地震预警系统为政府提供科学准确的数据和预警信息,帮助政府制定地震应对策略和灾后重建计划。
2. 公共影响力:地震预警系统的存在会增加公众对地震防灾减灾的认识和重视,提高国家的减灾意识和地震安全防范能力。
三、地震预警系统的发展前景目前,地震预警系统在世界范围内已经得到广泛应用,取得了一系列的成功案例。
然而,地震预警系统在技术上还面临着一些挑战,比如传感器的灵敏度、网络的稳定性等问题。
未来,随着技术的不断进步,地震预警系统将会更加完善,预警时间也会不断提高,为人们提供更大的安全保障。
什么是地震预警

什么是地震预警地震预警是指通过监测地下地震信号,提前预测地震发生的时间、地点及震级,并及时向可能受到影响的人群发出警报,以减少地震灾害造成的损失。
地震预警系统是利用地震波在地震发生后传播的速度快,比地震波到达地表前的电磁信号送达的速度快的特点,来提前几秒到几十秒的时间进行预警。
这个时间虽然很短,但可以让人们有足够的时间采取适当的措施,躲避地震带来的危害,从而最大限度地减少地震造成的人员伤亡和财产损失。
地震预警系统主要包括两个部分:地震监测和预警系统。
地震监测是指通过地震监测仪器对地下的震动信号进行监测,一旦发现地震信号,就会立即传送到地震预警系统中。
而地震预警系统则是利用地震监测仪器传来的地震信号,进行分析处理,提前预测地震的发生时间、地点及震级,并向可能受到影响的人群发出警报。
这两个系统密切配合,才能够有效地实现地震预警的目的。
目前,世界上有许多国家都在研究和开发地震预警系统。
日本是世界上最早建成并具有较为成熟的地震预警系统的国家之一。
日本的地震预警系统在2007年正式启用,至今已有十多年的历史。
该系统主要是由日本气象厅和日本地震研究所合作开发和维护的。
美国、中国、墨西哥等国家也都在积极开展地震预警系统的研究和建设工作。
地震预警系统的建设和运行离不开先进的科学技术。
近年来,随着科学技术的不断进步,地震预警系统的预警时间和准确性都得到了大幅提升。
目前,一般来说,地震预警系统的预警时间可以提前几秒到几十秒,这对于地震灾害防治来说已经是非常宝贵的时间。
而且,随着先进技术的应用,地震预警系统的预警准确性也将不断提高,能够更准确地预测地震的发生时间、地点和震级。
地震预警系统在地震灾害防治中具有重要的意义。
它可以为受地震影响的人群提供宝贵的逃生时间,减少地震灾害可能造成的人员伤亡和财产损失。
地震预警系统也可以为国家和地方政府提供决策依据,帮助他们及时调动救援力量,做好地震灾害的应对准备。
虽然地震预警系统还面临着一些挑战,但随着科学技术日益发展,相信地震预警系统的预警时间和准确性会不断提高,为人们提供更好的地震防治服务。
地震预警系统原理与应用

地震预警系统原理与应用一、引言地震是一种自然灾害,给人类社会和人民生命财产安全带来严重威胁。
为了能够提前预警地震并采取相应的措施,地震预警系统应运而生。
地震预警系统通过监测地震波在地球内部传播的速度和强度,及时预测地震发生的位置和强度,并发出预警信息,以便人们有时间采取避险措施。
本文将介绍地震预警系统的原理和应用。
二、地震预警系统的原理监测设备地震预警系统需要通过一系列的监测设备来收集地震相关数据。
其中包括地震仪、加速度计、倾斜计、GPS等设备。
这些设备能够准确测量地面的振动、倾斜和位移等数据,从而为预测地震提供支持。
数据处理收集到的地震数据需要经过复杂的算法和模型进行处理。
首先,需要对数据进行滤波处理,去除噪声和干扰。
然后,使用地震波传播模型,计算出地震波从发生位置到监测点的传播时间和路径。
最后,根据传播时间和路径,可以推算出地震的发生位置和强度。
预警模型根据处理过的数据,预警模型可以分析地震的发生概率和可能的强度范围。
这一过程通常涉及到复杂的统计分析和机器学习算法。
通过对历史地震数据的研究和分析,可以建立起合理的预警模型,并不断优化和更新模型参数。
预警信息发布当地震预警系统确认有地震将要发生时,会立即发出预警信息。
这些信息可以通过各种渠道传递给相关部门和民众,在最短时间内传达到各个地区。
同时,还可以将预警信息与其他应急系统进行联动,以便更好地组织救援行动。
三、地震预警系统的应用社会防灾减灾地震预警系统能够提供宝贵的时间窗口,让人们有足够的时间进行疏散和防护措施。
在强烈地震即将发生时,人们可以通过接收到的预警信息及时采取避险行动,减少伤亡和财产损失。
建筑结构安全保障利用地震预警系统提供的信息,可以对建筑结构进行调整和优化设计,增强建筑物的抗震能力。
同时,在建筑物设有智能感知装置时,也能实现自动关闭电梯、停止高风险操作等功能,保障人员安全。
交通运输安全保障交通运输是社会生活中不可或缺的一环,然而在地震发生之际也容易造成车辆事故等危险情况。
地震预警系统

地震预警
1
现状
2
方案
3
困难
4
进展
5
完善预警系统
地震预警系统中国虽然是个多地震国家,由地震造成的人员伤亡与经济损失巨大,但除大亚湾核电站在法国 人承建时建立了一个由地震监测络和人工决策相结合的地震预警系统外,中国尚未自主建设过其他重大工程地震 预警系统,有关研究工作也仅是刚刚在个别高校和研究所兴起。尽管地震预警在国外已有近50年的实践历史,但 在中国无论从理论还是实践上都是一片空白。强震动数据的实时处理与地震三要素的快速确定;地震动场的生成; 基于地震动参数的震害快速评估等都是我们需要进一步研究的科学和技术问题。
此外,预警系统面临一个尴尬的规律:越是地面运动强烈的极震区,能提供预警的时间就越短;对预警系统 依赖越弱的地区,能提供的预警时间反而越长。再拿汶川地震举两个极端的例子:离震中不到20公里的映秀镇, 处于预警系统的响应盲区,基本没有可能获得提前预警;而距离震中约1500公里的北京,可获得大约3分钟的提 前预警,但又几乎没有意义。
例如:地震波从震中传到北川县城大概需要25秒。
系统效果
美国
日本
中国
预警系统的原理决定了地震预警系统能够提供的应急时间是有上限的。美国虽然没有部署地震预警系统,但 相关研究已经开展了很多年,其中包括一个在旧金山湾区进行研究的名为ElarmS的地震预警系统。结果表明,这 套ElarmS预警系统,对于不到一半的地震,能够提供10秒以上的预警时间;对于绝大多数地震,能够提供的有效 预警时间不超过30秒。在几秒至数十秒的时间内,我们能够采取什么样的措施减少损伤?停止高速列车、从电梯 撤离、终止或保护关键仪器和设备、人员撤离到安全地带等等……我们可以做的很多,但是我们不能做的却更多。
- 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。
Study of the seismic system E-government based onCloud ComputingLi Zhitao, Fu Jihua,Wang Jianjun, Tan QiaoEarthquake information network laboratoryThe Institute of Crustal DynamicsBeijing China 100085zhitao.lee@Abstract—The traditional IT industry and the mode of E-Government are currently experiencing great changes, Cloud Computing becomes a trend. This paper explains the definition and understanding of the Cloud Computing. Combined with the demands of the seismic system E-government, such as high-performance computing, resource sharing service, building the green network, this paper analyzed the key technology of deployment the Cloud Computing in the seismic system and promoted the application mode.Keywords-Cloud Computing; visualization; cloud application model;data centerI.I NTRODUCTIONThe sharing of the network resources and computing capability is one of the most importing researches around the Internet community in the whole world. The utility of the Internet computing and storage resources stand in an unbalance status. How to achieve a balance of resources and computing power application and how to cope the growing trend of the data amount are both the need to be resolved. Cloud computing is in this context that shape.Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources such as networks, servers, storage, applications, and services. These resources can be rapidly provisioned and released from the Cloud with minimal management effort and little service provider interaction. This definition states that clouds have five essential characteristics: on-demand self-service, broad network access, resource polling, rapid elasticity, and measured service. For this features of Cloud Computing, the data center is more similar with the Internet. This made the resource switch to the demand applications, and access the computer or storage system according to different demand.How introduce Cloud Computing to the seismic system to promote the current E-Government standard in order to provide more IT services? This article is from this starting, discussing the network architecture of Cloud Computing using in the seismic system. The rest part of this paper is organized as follows: section Ⅱ introduces the background knowledge of Cloud Computing, section Ⅲ analyses the typical applications; then promotes the network architecture of Cloud computing using in seismic system in section Ⅳ. Finally, draw the conclusion in section Ⅴ.II.B ACKGROUND K NOWLEDGEA.The concept of Cloud ComputingCloud Computing with the interpretation of divergent viewsis still a lack of standardization definitions. But usually that: Cloud Computing distributes the tasks into the resource pool to make each application system acquire computing ability, storage space and all kinds of services as needed. This resource pool is called “Cloud”. “Cloud” is a number of self-maintenance and self-management virtual computing resources, usually being some large-scale server clusters, including computing servers, storage servers and so on. Cloud Computing collects all the computing resources to achieve automated management by software, without any human involvement.Cloud Computing is the development of Parallel Computing, Distributed Computing and Grid Computing, alsoit is the commercial realization of these computer science concepts. Cloud Computing is the evolution result of these concepts such as: Virtualization, Utility Computing, Infrastructure-as-a-Service, Platform-as-a-Service and Software-as-a-Service.B.The Features of Cloud ComputingCloud Computing is one of the computing technology based on the Internet which has the following characteristics:1. Very large scale, “Cloud” has a considerable scale. Google’s Cloud computing center already has more than 100 million servers. The “Cloud” of other corporations such as Amazon, IBM, Microsoft, have hundreds of thousands of servers also. Enterprise Private Cloud normally has hundreds or thousands of servers. “Cloud” can provide users an unprecedented computing power.2 Virtualization, Cloud Computing supports users in any location with any terminal to access to the application services. The requested resource is from the “Cloud” rather than a fixed physical entity. Application runs in “Cloud” somewhere, butin fact the users do not need to know or worry about the specific location of running it. Only with a laptop or a cell phone, the users can achieve anything they need including the super-computing task through the Web Services, this feature is shown in Figure 1.This research was supported by Research grant from Institute of CrustalDynamics, China Earthquake Administration (No.ZDJ2009-21) and theNFS(50908215)of China2010 International Conference on E-Business and E-GovernmentFigure 1 The application of Cloud Computing3. High reliability, “Cloud” uses many methods to protect the validity of services, such as multiple copies of data on fault-tolerant, computing nodes with the same structure being interchanged and so on.4. On-demand service, “Cloud” is a huge resource pool, the users buy these service on-demand. Cloud can run like water, electricity, gas and can bill according traffic.5. Low price, as the “Cloud” has the special fault-tolerancemeasures, it can be composed with the low-cost nodes. The “Cloud” automatic centralized management make the enterprise not need loading the increasing expensive data centermanagement costs. “Cloud” universal nature of the resource utilization compared to traditional systems significantly improved so that users can fully enjoy the “Cloud” of low-cost advantage.III. T HE TIPICAL EXAMPLES OF C LOUD COMPUTINGAPPLICATIONS Many manufacturers have involved in cloud computing field in some way. Google is one of the well-known competitors. To enter the field of cloud computing other vendors are IBM, Amazon and so on.A. Google’s Cloud ComputingGoogle’s Cloud computing technology is actually aimed at specific web applications and customized. For the large-scale feature of internal network data, Google proposed a set of parallel cluster approach based on distributed infrastructures which use the software’s ability to deal with cluster frequent node failure problem [1].Google’s cloud computing infrastructures model composed with four independent but closely linked systems. They are Google File System [2] based on the cluster file system, Google Map/Reduce programming model [3] raised according the characteristics of the applications, a distributed locking mechanism called Chubby[4], Google’s BigTable [5] which is a simplified model of large-scale distributed database.In addition to these four major parts, Google has also set up to build other cloud computing, including an area of service description language, as well as distributed locking mechanism. Literature [1] described the Google cluster approach within the building, using a large number of x86 server clusters to build the entire computing hardware infrastructure. Sawzall is a kindof language based on the Map/Reduce, which is used for large-scale information processing. Chubby is a high-availability, distributed data lock services previously cited. When the machine fails, Chubby uses the Paxos algorithm to ensure the consistency of the backup. Each unit of Chubby’s small distributed file system can be used to provide a locking mechanism.B. IBM’s Blue CloudIBM’s Blue Cloud computing platform make the Internet technology extend to the enterprise, so that the data center application can work like the Internet environment. Blue Cloud architecture can be applied to a number of scenarios: development and testing center, innovation centers, high performance computing center, enterprise data centers.Blue Cloud using the large-scale IBM computing technology, combining with IBM’s own hardware and software systems and services technology, supports open standards andopen source software. Blue Cloud basing on IBM Almaden Research Center’s cloud infrastructure, adopts virtualization software such as Xen and PowerVM, linux operation systemimages and Hadoop parallel software systems to build. Blue Cloud can help users to build cloud computing environments, which is through Tivoli, DB2, WebSphere to complete thehardware integration. Blue Cloud can help the enterprisessetting up a distributed, global accessing resource structure.Figure 2 IBM Blue Cloud ArchitectureFigure 2 shows the Blue Cloud product architecture. You can see, Blue Clue computing platform consists of a data center including IBM Trivoli Software Development Manager, IBM Tivoli monitoring software, IBM WebSphere Application Server, IBM DB2 database as well as some components of a common form of virtualization.Blue Cloud’s hardware platform is not any special place, but the Blue Cloud software platform is different from the pre-distributed platform, mainly reflected in the use of virtual machine as well as for large-scale data processing software Apach Hadoop’s deployment.C. Amazon’s Cloud ComputingAmazon called its Cloud Computing platform the Elastic Compute Cloud (referred to as EC2), which is the first corporation to provide remote computing services [6].Amazon’s Elastic Compute Cloud is established on the large-scale cluster computing platform within its own company, the users can operate its instance through the Elastic Compute Cloud’s network interface. Users pay only for the computing platform used by instances of payment, to run after the billing has come to an end. Instances mentioned here are controlled to run a task of a complete virtual machine. In this way, the users do not have to build their own cloud computing platform, saving equipment and maintenance costs.Amazon’s Elastic Computing Cloud developed from the exiting platform of Amazon Web services. In March 2006, Amazon launched Simple Storage Service (being called S3), the users using SOAP protocol to store and access their own data object. In July 2007, Amazon launched the Simple Queue Service (being called SQ3), this service can make a virtual host messages sent between the hosts to support data transformation between distributed processes without having to consider the issue of lost message. Amazon has continued to provide EBS (elastic block storage) services to provide users with block-level storage interface. In the provision of such infrastructure at the same time, Amazon’s Elastic Compute Cloud EC2 has developed a system that is open to outside developers.All in all, Amazon meets the cluster system demand of small-scale software developers by providing the elastic computing cloud, meanwhile reducing their maintenance burden. In order to further development of Elastic Compute Cloud, Amazon planned how to help the users to develop network applications on the cloud computing platform. In addition to E-Business, Cloud computing is also Amazon’s core value. It must be added more network service components modules on the elastic cloud computing platform to help the users to build the computing environment with ease.IV.T HE E –G OVERNMET BASED ON C LOUD C OMPUTINGWITHIN SEISMIC SYSTEMThrough a variety of application example of cloud computing research, combined with the characteristics of seismic system, I believe that hybrid cloud model is suitable for deployment in the earthquake. What is mixed-cloud model? Refers to the establishment of private cloud in the industry, seismic units within the system can combine the characteristics of their own private cloud deployment of different functions, such as high-performance computing cloud, innovation cloud, IDC cloud, and so software development cloud. At the same time, the various units within the system can interact with the private cloud associated with the public cloud in order to meet unexpected business needs.Figure 3 The hybrid cloud modelFigure 3 shows a hybrid cloud model, the various boards within the system established their own private cloud. Each private cloud connected through high-speed network. Such cooperation is conducive to scientific research units to carry our high-performance computing, but also makes the sharing of resources more convenient and safe. In addition, the private connected to some public clouds also. If the data within the system can not meet the excessive demand, it is easy to use public resources to enhance the seismic industry satisfaction with public services.In this paper, to the institute of Crustal Dynamics’s cloud computing center, for example, discusses its model structure. I propose the use of IBM’s Blue Cloud platform. Because of its well against the existing IT infrastructure consolidation through virtualization and automation technologies, to build new data center hardware and software resources to achieve unified management, unified distribution, unified deployment, unified monitoring and unified backup, breaking the monopoly of resources in a single operation, thus helping centers achieve the requirements of various application systems.Figure 4 shows the logic of private cloud topology. Users can submit a request through the server interface to define their own virtual body into a fit, such as server configuration, number, storage type, network environment, meanwhile the life cycle of each request is maintained by the platform. Overall system architecture includes hardware, software and services in three parts. Hardware is mainly x86 series machines or blade servers. Software components include the automatic management system and management center software required to run day to day. Server’s components include the computing data center operations and maintenance system.The monitoring and controlling of the whole system is realized in the management platform. Users can see all the hardware resources, no mater from which fraternal institutions, no matter what type, can be under unified management. Other management services such as user management, backup management, security management, all can be achieved here. In addition, the capacity management can define resources and applications, the environmental monitoring module is used to monitor the entire bureau center of the environment, software management module will integrate all applications for a resource library to achieve software management anddistribution and so on, the customer center management function is used to maintaining the entire data center customers.Seismic system constructs the E-Government based on the cloud computing has many advantages as follows, providing high-performance computing, coping with sudden great increasing network traffic caused by an earthquake, establishment of collaborative research environment, supplyingseismic data-sharing services, construction seismic science and technology network, building green seismic networkenvironment construction and so on.Figure 4 The logic of the data center topologyV. C ONCLUSIONS AND FUTURE WORKThis article describes the characteristics of cloud computingconcept and a detailed analysis of the current more mature commercial cloud computing model. On this basis, the establishment of seismic system E-Government based on hybrid cloud computing model is proposed to provide the ITservices and promote the scientific computing ability. Believed that with the concept of cloud computing and the corresponding proposed system builds practical experience wasgained, in the near future, cloud computing will become an academic and industry research focus.R EFERENCES[1] Barroso LA, Dean J, Holzle U. Web search for a planet: The Googlecluster architecture. IEEE Micro, 2003,23(2):22-28[2] Ghemawat S, Gobioff H, Leung ST. The Google file system. In : Proc.Of the 19th ACM Symp. On Operating Systems Principles. New York: ACM Press, 2003. 29-43[3] Dean J, Ghemawa S, MapReduce: Simplified data processing on largeclusters, In: Proc. Of the 6th Symp. On Operating System Design and Implementation. Berkeley: USENIX Association, 2004. 137-150.[4] Burrows M. The clubby lock service for loosely-coupled distributedsystems, In: Proc. Of the 7th USENIX Symp. On Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006. 335-350.[5] Chang F, Dean J, Ghemawat S, Hsieh WC, Wallach DA, Burrows M,Chandra T, Fikes A, Gruber RE. Bigtable: A distributed storage system for structured data. In: Proc. Of the 7th USENIX Symp. On Operating Systems Design and Implementation. Berkeley: USENIX Association, 2006.205-218[6] Amazon Elastic Compute Cloud. 。